﻿* Encoding: UTF-8.
****DYOR Perception Research Note****


***FILTERS: screen out those who spent less than 1.5 seconds per item (26 seconds total) on Q10 belief battery*** 
***belief timing****

FREQUENCIES page_Q10_grid_timing. 
DESCRIPTIVES page_Q10_grid_timing. 


DATASET ACTIVATE DataSet1.
USE ALL.
COMPUTE filter_$=(page_Q10_grid_timing  > 25.5).
VARIABLE LABELS filter_$ 'page_Q10_grid_timing  > 25.5 (FILTER)'.
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'.
FORMATS filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE.

FILTER OFF.
USE ALL.
EXECUTE.

COMPUTE attnckW1 = filter_$. 
FREQUENCIES attnckW1. 
DESCRIPTIVES attnckW1. 

FREQUENCIES page_Q10_grid_w2_timing.
DESCRIPTIVES page_Q10_grid_w2_timing.

RECODE page_Q10_grid_w2_timing (SYSMIS = 0). 
FREQUENCIES page_Q10_grid_w2_timing.

USE ALL.
COMPUTE filter_$=((page_Q10_grid_w2_timing > 25.5) OR (page_Q10_grid_w2_timing < 1)).
VARIABLE LABELS filter_$ '(page_Q10_grid_w2_timing > 25.5) OR (page_Q10_grid_w2_timing < 1) '+
    '(FILTER)'.
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'.
FORMATS filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE.

FILTER OFF.
USE ALL.
EXECUTE.

COMPUTE attnckW2 = filter_$. 
FREQUENCIES attnckW2. 
DESCRIPTIVES attnckW2. 

COMPUTE attnch = (attnckW1 + attnckW2). 
FREQUENCIES attnch. 
MISSING VALUES attnch (0,1). 
FREQUENCIES attnch. 

USE ALL.
COMPUTE acfilter=(attnch = 2).
VARIABLE LABELS acfilter 'attnch = 2 (FILTER)'.
VALUE LABELS acfilter 0 'Not Selected' 1 'Selected'.
FORMATS acfilter (f1.0).
FILTER BY acfilter.
EXECUTE.

***Demographics from YouGoV***
    gender race educ faminc_new pid3 pid7 ideo5 pew_churatd pew_bornagain pew_religimp
    ***use for controls: age women white educ party*** 

FREQUENCIES birthyr. 
COMPUTE age = (2021-birthyr). 
FREQUENCIES age. 
Descriptives age. 

FREQUENCIES gender. 
COMPUTE women = gender. 
RECODE women (1=0) (2=1).
VALUE LABELS women 0 'men' 1 'women'. 
FREQUENCIES women. 

FREQUENCIES race.
COMPUTE white = race. 
RECODE white (1=1) (ELSE=0).
VALUE LABELS white 0 'other' 1 'white'. 
FREQUENCIES white. 


COMPUTE black = race. 
RECODE black (2=1) (ELSE=0).
VALUE LABELS black 0 'other' 1 'black'. 
FREQUENCIES black. 

COMPUTE hispanic = race. 
RECODE hispanic (3=1) (ELSE=0).
VALUE LABELS hispanic 0 'other' 1 'hispanic'. 
FREQUENCIES hispanic. 

FREQUENCIES educ. 
COMPUTE educate = educ.
FREQUENCIES educate. 


FREQUENCIES pid7. 
COMPUTE party = pid7. 
MISSING VALUES party (8,9). 
VALUE LABELS party 1 'Strong Democrat' 2 'Democrat' 3 'Lean Democrat' 4 'Independent' 5 'Lean Republican' 6 'Republican' 7 'Strong Republican'. 
FREQUENCIES party. 
Descriptives party. 

         

***W1 interest in news politics***

FREQUENCIES Q1a Q1b.
COMPUTE newsatt = Q1a. 
COMPUTE polinter = Q1b. 
VARIABLE LABELS
newsatt 'How closely do you follow news and information about current events?' 
polinter 'More generally, how interested are you in politics?'.
FREQUENCIES newsatt polinter. 

COMPUTE polint = MEAN(newsatt, polinter). 
DESCRIPTIVES polint.
CORRELATIONS newsatt polinter. 

****W1 DYOR variables***
    
FREQUENCIES Q7_a Q7_b Q7_c.
COMPUTE dyor1 = Q7_a. 
COMPUTE dyor2 = Q7_b. 
COMPUTE dyor3 = Q7_c. 
VARIABLE LABELS
dyor1 'Anyone can be an expert on something if they do enough research'
dyor2 'I prefer to do my own research rather than rely on experts'
dyor3 'The opinions of people who have done their own research are just as valid as the opinions of experts'.
FREQUENCIES dyor1 dyor2 dyor3. 

CORRELATIONS dyor1 dyor2 dyor3. 

RELIABILITY
  /VARIABLES= dyor1 dyor2 dyor3
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA
  /SUMMARY=TOTAL.

COMPUTE dyorw1 = MEAN(dyor1, dyor2, dyor3). 
DESCRIPTIVES dyorw1. 

****W2 DYOR variables***
    
FREQUENCIES Q7_a_w2 Q7_b_w2 Q7_c_w2.
COMPUTE dyor1w2 = Q7_a_w2. 
COMPUTE dyor2w2 = Q7_b_w2. 
COMPUTE dyor3w2 = Q7_c_w2. 
VARIABLE LABELS
dyor1w2 'Anyone can be an expert on something if they do enough research'
dyor2w2 'I prefer to do my own research rather than rely on experts'
dyor3w2 'The opinions of people who have done their own research are just as valid as the opinions of experts'.

FREQUENCIES dyor1w2 dyor2w2 dyor3w2.

CORRELATIONS dyor1w2 dyor2w2 dyor3w2.

RELIABILITY
  /VARIABLES= dyor1w2 dyor2w2 dyor3w2 
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA
  /SUMMARY=TOTAL.

COMPUTE dyorw2 = MEAN(dyor1w2, dyor2w2, dyor3w2). 
DESCRIPTIVES dyorw2. 


***W1 trust in science and expertise***

FREQUENCIES Q20_g Q20_h Q20_i Q20_q. 
COMPUTE ITuni = Q20_g. 
COMPUTE ITscience = Q20_h. 
COMPUTE ITmed = Q20_i. 
COMPUTE ITcdc= Q20_q. 
VARIABLE LABELS
ITuni 'colleges and universities'
ITscience 'scientists'
ITmed 'doctors and medical scientists'
ITcdc 'the cdc'.
FREQUENCIES  ITuni ITscience ITmed ITcdc. 

RELIABILITY
  /VARIABLES= ITuni ITscience ITmed ITcdc
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

COMPUTE scitrustw1 =  MEAN(ITuni, ITscience, ITmed, ITcdc). 
DESCRIPTIVES scitrustw1. 

***W2 trust in science and expertise***

FREQUENCIES Q20_g_w2 Q20_h_w2 Q20_i_w2 Q20_q_w2. 
COMPUTE ITuniw2 = Q20_g_w2. 
COMPUTE ITsciencew2 = Q20_h_w2. 
COMPUTE ITmedw2 = Q20_i_w2. 
COMPUTE ITcdcw2= Q20_q_w2. 
VARIABLE LABELS
ITuniw2 'colleges and universities'
ITsciencew2 'scientists'
ITmedw2 'doctors and medical scientists'
ITcdcw2 'the cdc'.
FREQUENCIES  ITuniw2 ITsciencew2 ITmedw2 ITcdcw2. 

RELIABILITY
  /VARIABLES= ITuniw2 ITsciencew2 ITmedw2 ITcdcw2
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

COMPUTE scitrustw2 =  MEAN(ITuniw2, ITsciencew2, ITmedw2, ITcdcw2). 
DESCRIPTIVES scitrustw2.


****W1 Covid beliefs****

FREQUENCIES Q15_a Q15_b Q15_c Q15_d Q15_e Q15_f Q15_g Q15_h Q15_i.
COMPUTE cvBF2 = Q15_b. 
COMPUTE cvBF3 = Q15_c. 
COMPUTE cvBF8 = Q15_h. 
RECODE Q15_a  (1=5) (2=4) (3=3) (4=2) (5=1) into cvBF1. 
RECODE Q15_d (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF4. 
RECODE Q15_e (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF5. 
RECODE Q15_f (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF6. 
RECODE Q15_g (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF7. 
RECODE Q15_i (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF9. 

FREQUENCIES cvBF1 cvBF2 cvBF3 cvBF4 cvBF5 cvBF6 cvBF7 cvBF8 cvBF9. 
COMPUTE cvBFw1 = MEAN(cvBF1, cvBF2, cvBF3, cvBF4, cvBF5, cvBF6, cvBF7, cvBF8, cvBF9). 

DESCRIPTIVES cvBFw1. 

RELIABILITY
  /VARIABLES= cvBF1 cvBF2 cvBF3 cvBF4 cvBF5 cvBF6 cvBF7 cvBF8 cvBF9
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.


***W2 Covid beliefs****

FREQUENCIES Q15_a_w2 Q15_b_w2 Q15_c_w2 Q15_d_w2 Q15_e_w2 Q15_i_w2 Q15_j_w2 Q15_k_w2 Q15_l_w2. 

COMPUTE cvBF2w2 = Q15_b_w2. 
COMPUTE cvBF3w2 = Q15_c_w2. 
COMPUTE cvBF11w2 = Q15_k_w2. 
COMPUTE cvBF12w2 = Q15_l_w2. 
RECODE Q15_a_w2  (1=5) (2=4) (3=3) (4=2) (5=1) into cvBF1w2. 
RECODE Q15_d_w2 (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF4w2. 
RECODE Q15_e_w2 (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF5w2. 
RECODE Q15_i_w2 (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF9w2.  
RECODE Q15_j_w2 (1=5) (2=4) (3=3) (4=2) (5=1)  into cvBF10w2. 

FREQUENCIES cvBF1w2 cvBF2w2 cvBF3w2 cvBF4w2 cvBF5w2 cvBF9w2 cvBF10w2 cvBF11w2 cvBF12w2. 
COMPUTE cvBFw2= MEAN(cvBF1w2, cvBF2w2, cvBF3w2, cvBF4w2, cvBF5w2, cvBF9w2, cvBF10w2, cvBF11w2, cvBF12w2). 

DESCRIPTIVES cvBFw2. 

RELIABILITY
  /VARIABLES= cvBF1w2 cvBF2w2 cvBF3w2 cvBF4w2 cvBF5w2 cvBF9w2 cvBF10w2 cvBF11w2 cvBF12w2
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

****W1 Covid Concerns****

FREQUENCIES Q16_a Q16_b Q16_c Q16_d. 
COMPUTE cvrisk1 = Q16_a. 
COMPUTE cvrisk2 = Q16_b. 
COMPUTE cvrisk3 = Q16_c. 
COMPUTE cvrisk4 = Q16_d. 
FREQUENCIES cvrisk1 cvrisk2 cvrisk3 cvrisk4. 

CORRELATIONS cvrisk1 cvrisk2 cvrisk3 cvrisk4. 

RELIABILITY
  /VARIABLES= cvrisk1 cvrisk2 cvrisk3 cvrisk4
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

***heath concerns***

COMPUTE CVriskw1a = MEAN(cvrisk1, cvrisk2).  

***Economic concerns***

COMPUTE CVriskw1b = MEAN(cvrisk3, cvrisk4). 

DESCRIPTIVES cvriskw1a cvriskw1b. 



****W2 Covid Concerns****

FREQUENCIES Q16_a_w2 Q16_b_w2 Q16_c_w2 Q16_d_w2. 
COMPUTE cvrisk1w2 = Q16_a_w2. 
COMPUTE cvrisk2w2 = Q16_b_w2.
COMPUTE cvrisk3w2  =Q16_c_w2.
COMPUTE cvrisk4w2 = Q16_d_w2.
FREQUENCIES cvrisk1w2 cvrisk2w2 cvrisk3w2 cvrisk4w2. 

RELIABILITY
  /VARIABLES= cvrisk1w2 cvrisk2w2 cvrisk3w2 cvrisk4w2
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

COMPUTE CVriskw2a = MEAN(cvrisk1w2, cvrisk2w2). 
COMPUTE CVriskw2b = MEAN(cvrisk3w2, cvrisk4w2). 

DESCRIPTIVES cvriskw2a CVriskw2b. 
CORRELATIONS cvrisk1w2 cvrisk2w2 cvrisk3w2 cvrisk4w2. 



****news media use measures****
***W1 news media use***

FREQUENCIES Q2_a Q2_b Q2_c Q2_d Q2_e Q2_f Q2_g Q2_h Q2_i Q2_j.
RENAME VARIABLES (Q2_a Q2_b Q2_c Q2_d Q2_e Q2_f Q2_g Q2_h Q2_i Q2_j = tvnews localtv localnp fox cnn msnbc natnp onlinenews 
mobilenews searchnews). 
VARIABLE LABELS
tvnews 'National nightly television news on ABC, CBS, NBC, or PBS'
localtv ' Local television news'
localnp 'Local or regional newspapers (online or in print)'
fox 'Fox News (online or on TV)'
cnn 'CNN (online or on TV)'
msnbc 'MSNBC (online or on TV)'
natnp 'National newspapers (online or in print)'
onlinenews 'Online news sites'
mobilenews 'Mobile news apps on a phone or tablet (such as Apple News or Google News)'
searchnews 'Search engine (such as Google or Bing)'. 
FREQUENCIES tvnews localtv localnp fox cnn msnbc natnp onlinenews mobilenews searchnews.

COMPUTE tradnewsW1 = MEAN(tvnews, localtv, localnp, natnp). 
DESCRIPTIVES tradnewsW1 tradnewsW2.  

RELIABILITY
  /VARIABLES= tvnews localtv localnp natnp
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

COMPUTE olnewsW1 = MEAN(onlinenews, mobilenews, searchnews).

RELIABILITY
  /VARIABLES= onlinenews mobilenews searchnews
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

***W1 social media use***

FREQUENCIES Q4_a Q4_b Q4_c Q4_d Q4_e Q4_f Q4_g. 
RENAME VARIABLES (Q4_a Q4_b Q4_c Q4_d Q4_e Q4_f Q4_g = smnews smff smsci smhealth smcon sminsp smadvice). 
VARIABLE LABELS
smnews 'To get news or information about politics'
smff 'To connect with friends and family'
smsci 'To get news or information about science' 
smhealth 'To get news or information about health'
smcon 'To connect with people or communities who share your interests'
sminsp 'To get inspiration from brands, celebrities, artists, or influencers'
smadvice 'To get tips, advice, or ideas on topics like health, fitness, parenting, hobbies, or other interests'.
FREQUENCIES smnews smff smsci smhealth smcon sminsp smadvice. 


COMPUTE sminfo = MEAN(smnews, smsci, smhealth). 

FREQUENCIES sminfo. 
DESCRIPTIVES sminfo. 

RELIABILITY
  /VARIABLES= smnews smsci smhealth
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

***Wave 2 news media use***


FREQUENCIES Q2_a_w2 Q2_b_w2 Q2_c_w2 Q2_d_w2 Q2_e_w2 Q2_f_w2 Q2_g_w2 Q2_h_w2 Q2_i_w2 Q2_j_w2.
RENAME VARIABLES (Q2_a_w2 Q2_b_w2 Q2_c_w2 Q2_d_w2 Q2_e_w2 Q2_f_w2 Q2_g_w2 Q2_h_w2 Q2_i_w2 Q2_j_w2= 
tvnewsW2 localtvW2 localnpW2 foxW2 cnnW2 msnbcW2 natnpW2 onlinenewsW2 mobilenewsW2 searchnewsW2). 
VARIABLE LABELS
tvnewsW2 'National nightly television news on ABC, CBS, NBC, or PBS'
localtvW2 ' Local television news'
localnpW2 'Local or regional newspapers (online or in print)'
foxW2 'Fox News (online or on TV)'
cnnW2 'CNN (online or on TV)'
msnbcW2 'MSNBC (online or on TV)'
natnpW2 'National newspapers (online or in print)'
onlinenewsW2 'Online news sites'
mobilenewsW2 'Mobile news apps on a phone or tablet (such as Apple News or Google News)'
searchnewsW2 'Search engine (such as Google or Bing)'. 
FREQUENCIES tvnewsW2 localtvW2 localnpW2 foxW2 cnnW2 msnbcW2 natnpW2 onlinenewsW2 mobilenewsW2 searchnewsW2.

COMPUTE tradnewsW2 = MEAN(tvnewsW2, localtvW2, localnpW2, natnpW2). 

RELIABILITY
  /VARIABLES= tvnewsW2 localtvW2 localnpW2 natnpW2
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

COMPUTE olnewsW2 = MEAN(onlinenewsW2, mobilenewsW2, searchnewsW2).

RELIABILITY
  /VARIABLES= onlinenewsW2 mobilenewsW2 searchnewsW2
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.
    

***W2 social media use***

FREQUENCIES  Q4_a_w2 Q4_b_w2 Q4_c_w2 Q4_d_w2 Q4_e_w2 Q4_f_w2 Q4_g_w2.  
RENAME VARIABLES (Q4_a_w2 Q4_b_w2 Q4_c_w2 Q4_d_w2 Q4_e_w2 Q4_f_w2 Q4_g_w2 = smnewsW2 smffW2 smsciW2 smhealthW2 smconW2 sminspW2 smadviceW2). 
VARIABLE LABELS
smnewsW2 'To get news or information about politics'
smffW2 'To connect with friends and family'
smsciW2 'To get news or information about science' 
smhealthW2 'To get news or information about health'
smconW2 'To connect with people or communities who share your interests'
sminspW2 'To get inspiration from brands, celebrities, artists, or influencers'
smadviceW2 'To get tips, advice, or ideas on topics like health, fitness, parenting, hobbies, or other interests'.
FREQUENCIES smnewsW2 smffW2 smsciW2 smhealthW2 smconW2 sminspW2 smadviceW2. 

COMPUTE sminfow2 = MEAN(smnewsw2, smsciw2, smhealthw2)/3. 

FREQUENCIES sminfow2. 
DESCRIPTIVES sminfow2. 

RELIABILITY
  /VARIABLES= smnewsW2 smsciW2 smhealthW2
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.


****Analyses****
    
****Demographic predictors***

REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT dyorw1
  /METHOD=ENTER age women white black hispanic educate party polint tradnewsW1 olnewsW1 sminfo. 

***DYOR and sci trust***

REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT scitrustw2
  /METHOD=ENTER age women white educate party polint tradnewsW1 olnewsW1 sminfo scitrustw1 
    /METHOD=ENTER dyorw2.  

***DYOR and covid beliefs***

REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvBFw2
  /METHOD=ENTER age women white educate party polint tradnewsW1 olnewsW1 sminfo scitrustw1 cvBFw1 dyorw2.


***DYOR and covid concerns***

REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvriskw2a
  /METHOD=ENTER age women white educate party polint tradnewsW1 olnewsW1 sminfo scitrustw1 cvriskw1a
    /METHOD=ENTER dyorw2.


REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvriskw2b
  /METHOD=ENTER age women white educate party polint  tradnewsW1 olnewsW1 sminfo scitrustw1 cvriskw1b 
      /METHOD=ENTER dyorw2.


****Cross Sectional Analyses****

***DYOR and sci trust***

REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT scitrustw1
  /METHOD=ENTER age women white educate party polint tradnewsW1 olnewsW1 sminfo dyorw1.


REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT scitrustw2
  /METHOD=ENTER age women white educate party polint tradnewsW2 olnewsW2 sminfow2 dyorw2. 

***DYOR and covid beliefs***
    
REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvBFw1
  /METHOD=ENTER age women white educate party polint tradnewsW1 olnewsW1 sminfo scitrustw1 dyorw1.

REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvBFw2
  /METHOD=ENTER age women white educate party polint tradnewsW2 olnewsW2 sminfow2 scitrustw2 dyorw2.  

***DYOR and Covid concerns***
  
REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvriskw1a
  /METHOD=ENTER age women white educate party polint tradnewsW1 olnewsW1 sminfo scitrustw1 dyorw1.

REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvriskw2a
  /METHOD=ENTER age women white educate party polint tradnewsW2 olnewsW2 sminfow2 scitrustw2 dyorw2. 
  
  
REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvriskw1b
  /METHOD=ENTER age women white educate party polint tradnewsW1 olnewsW1 sminfo scitrustw1 dyorw1.

REGRESSION
  /DESCRIPTIVES MEAN STDDEV SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT cvriskw2b
  /METHOD=ENTER age women white educate party polint tradnewsW2 olnewsW2 sminfow2 scitrustw2 dyorw2. 
